NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 4 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
von Davier, Matthias; Tyack, Lillian; Khorramdel, Lale – Educational and Psychological Measurement, 2023
Automated scoring of free drawings or images as responses has yet to be used in large-scale assessments of student achievement. In this study, we propose artificial neural networks to classify these types of graphical responses from a TIMSS 2019 item. We are comparing classification accuracy of convolutional and feed-forward approaches. Our…
Descriptors: Scoring, Networks, Artificial Intelligence, Elementary Secondary Education
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Alhadi, Moosa A. A.; Zhang, Dake; Wang, Ting; Maher, Carolyn A. – North American Chapter of the International Group for the Psychology of Mathematics Education, 2022
This research synthesizes studies that used a Digitalized Interactive Component (DIC) to assess K-12 student mathematics performance during Computer-based-Assessments (CBAs) in mathematics. A systematic search identified ten studies that categorized existing DICs according to the tools that provided language assistance to students and tools that…
Descriptors: Computer Assisted Testing, Mathematics Tests, English Language Learners, Geometry
Mullis, Ina V. S., Ed.; Martin, Michael O., Ed.; von Davier, Matthias, Ed. – International Association for the Evaluation of Educational Achievement, 2021
TIMSS (Trends in International Mathematics and Science Study) is a long-standing international assessment of mathematics and science at the fourth and eighth grades that has been collecting trend data every four years since 1995. About 70 countries use TIMSS trend data for monitoring the effectiveness of their education systems in a global…
Descriptors: Achievement Tests, International Assessment, Science Achievement, Mathematics Achievement
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Pelánek, Radek; Rihák, Ji?rí – International Educational Data Mining Society, 2016
In online educational systems we can easily collect and analyze extensive data about student learning. Current practice, however, focuses only on some aspects of these data, particularly on correctness of students answers. When a student answers incorrectly, the submitted wrong answer can give us valuable information. We provide an overview of…
Descriptors: Foreign Countries, Online Systems, Geography, Anatomy